For various reasons, companies may sometimes attempt to migrate their data and their customers' data from one type of database to another. This may be done for business reasons, such as attempting to migrate users of a competitor's database to the company's own in-house database, or for technical reasons, such as improving performance or lowering cost (or any combination thereof). Whatever the reasons, there are often technical challenges in migrating the data from one database type to another database type. One such challenge is that the data itself as well as the schema for the data may need to be modified to fit a completely different database type. For example, when migrating data from an ordinary relational database management system to an in-memory database management system it is necessary to convert the data from being row-based to being column-based. Additionally, when dealing with data of customers, it may be important to perform the migration without any downtime, allowing the migration to be transparent (or nearly transparent) to the customers to ensure an optimal customer experience. Furthermore, the workload on the new database may be different than the workload on the old database (for example, certain commands may wind up putting more strain on the new database than the old database, making resource management important). These aspects, in addition to the typical desires of wanting to ensure data is migrated accurately and efficiently, can be challenging, especially when dealing with large databases.